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<h3>The Open-Source Dependency Toolkit: Roadmap</h3>

The following milestones are used to track the progress in the development of 
the Open-Source Dependency Toolkit (OSDT). The fact that a milestone is mentioned 
here does not guarantee that it will be implemented eventually, but merely 
indicates the possibility that we may undertake a research project in this direction.
If you wish to contribute to a particular milestone, or if you know somebody who does, 
please contact Matthias Buch-Kromann &lt;mbk.isv@cbs.dk&gt;.

<ul>
    <li> <b>Parsing (P):</b>
    <ul> 
        <li> <b>P1 (July 2009).</b> Non-projective dependency parsing with the edge-factored 
        model from McDonald (2006). 
        <li> <b>P2 (July 2009).</b> Projective dependency parsing with Model 2 from Collins (1997). 
        <li> <b>P3.</b> Non-projective dependency parsing of primary dependencies 
        with surface trees, deep roots, and punctuation using the dependency model 
        from Buch-Kromann (2006, ch. 6.2). 
        <li> <b>P4.</b> Like P3 but with secondary dependencies and gapping coordinations. 
    </ul>
    
    <li> <b>Learning (L):</b>
    <ul>
        <li> <b>L1 (July 2009).</b> Using existing learning paradigms from McDonald (2006) and
        Collins (1997). 
        <li> <b>L2 (2009).</b> XHPM estimation of conditional probability distributions.
        <li> <b>L3 (2009).</b> General modelling language, as in Buch-Kromann (2006, ch. 6.1).
    </ul>
    
    <li> <b>Morphological parsing (M):</b>
    <ul>
        <li> <b>M1.</b> Morphological parser with concatenative morphology
        and lexical transformations.
    </ul>

    <li> <b>Discourse parsing (D):</b> 
    <ul>
        <li> <b>D1.</b> Parsing discourse structures as dependency trees.
        <li> <b>D2.</b> Adding support for anaphora and discourse anaphora.
    </ul>

    <li> <b>Speech parsing (S):</b> 
    <ul>
        <li> <b>S1.</b> Parsing a speech lattice with transition probabilities.
        <li> <b>S2.</b> Parsing speech encoded as audio files (using some 
        appropriate speech analysis tool).
    </ul>
    
    
    <li> <b>Bitext parsing (B):</b> 
    <ul>
        <li> <b>B1.</b> Simple bitext parser based on the McDonald model, Giza++ word
        alignment model, translation unit size (based on Buch-Kromann 2007), and simple repairs.
        <li> <b>B2.</b> Bitext parser based on Buch-Kromann white paper (2007).
    </ul>
    
    
    <li> <b>Translation (T):</b> 
    <ul>
        <li> <b>T1.</b> Simple dependency tree-tree translation system, based on 
        output from bitext parser.
        <li> <b>T2.</b> String-tree translation system, using the parser to parse
        a translation word lattice for the source language. 
    </ul>    

    <li> <b>Eye-gaze modelling (E):</b> 
    <ul>
        <li> <b>E1.</b> Integrating parser with simple eye-gaze model using data
        from eye-tracker.
    </ul>
    
</ul>

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